a Department of Biomedical Engineering, Cockrell School of Engineering , The University of Texas at Austin , Austin , Texas , USA.
b Department of Internal Medicine, Division of Pulmonary and Sleep Medicine, McGovern School of Medicine , The University of Texas Health Science Center at Houston , Houston , Texas , USA.
Chronobiol Int. 2019 Jul;36(7):927-933. doi: 10.1080/07420528.2019.1596947. Epub 2019 Apr 16.
Elevated asleep heart rate (HR) is a risk factor for cardiovascular disease and other-cause morbidity and mortality. We assessed the accuracy of Fitbit Inc. PurePulse® photoplethysmography with reference to three-lead electrocardiography (ECG) in determining HR during sleep. HR of 35 (17 female) healthy adults 25.1 ± 10.6 years of age (mean ± SD) was continuously recorded throughout a single night of sleep. There was no significant difference in asleep HR mean (0.09 beats per minute [bpm], = 0.426) between Fitbit photoplethysmography and ECG; plus, there was excellent intraclass correlation (0.998) and narrow Bland-Altman agreement range (2.67 bpm). The regression analysis of Bland-Altman plot of mean asleep HR indicates Fitbit tends to slightly overestimate reference values in the lower range of HR (HR < 50 bpm) by 0.51 bpm and slightly underestimate reference values in the higher range of HR (HR > 80 bpm) by 0.63 bpm. Mixed model analysis of epoch-by-epoch (5-min epochs) asleep HR showed significant "U" shape trend ( < 0.001) in amount of Fitbit error (absolute amount of difference between ECG and Fitbit values regardless of overestimation or underestimation) in regard to HR, i.e. smaller error in the medium range of HR (60-80 bpm) and slightly larger error for lower (<60 bpm) and higher (>80 bpm) ranges of HR. However, effect of age, body mass index, gender, and subjective sleep quality measured by Pittsburgh sleep quality index (good/poor sleepers) on error in estimating HR by the Fitbit method was not significant. It is concluded that Fitbit photoplethysmography suitably tracks HR during sleep in healthy young adults.
静息心率(HR)升高是心血管疾病和其他原因发病率和死亡率的一个危险因素。我们评估了 Fitbit Inc. 的 PurePulse®光电容积脉搏波法通过参考三导联心电图(ECG)在确定睡眠期间 HR 的准确性。35 名(17 名女性)健康成年人的 HR,年龄 25.1±10.6 岁(平均值±标准差),在一整个晚上的睡眠中连续记录。Fitbit 光电容积脉搏波法和 ECG 之间的静息 HR 平均值(0.09 次/分钟[bpm], =0.426)没有显著差异;此外,组内相关系数非常高(0.998),Bland-Altman 一致性范围较窄(2.67 bpm)。静息 HR 平均 Bland-Altman 图的回归分析表明,Fitbit 在 HR 较低范围(HR<50 bpm)中略微高估参考值 0.51 bpm,在 HR 较高范围(HR>80 bpm)中略微低估参考值 0.63 bpm。逐epoch(5 分钟 epoch)静息 HR 的混合模型分析显示,HR 方面的 Fitbit 误差(ECG 和 Fitbit 值之间差异的绝对值,无论高估还是低估)呈显著的“U”形趋势(<0.001),即 HR 中等范围(60-80 bpm)的误差较小,而 HR 较低(<60 bpm)和较高(>80 bpm)范围的误差稍大。然而,年龄、体重指数、性别和匹兹堡睡眠质量指数(良好/较差睡眠者)主观睡眠质量对 Fitbit 法估计 HR 误差的影响不显著。结论是,Fitbit 光电容积脉搏波法在健康年轻成年人中适合跟踪睡眠期间的 HR。